Asset allocation constitutes one of the most crucial and most challenging tasks in financial engineering, which often requires the estimation of large covariance or precision matrices, from short time-span multivariate observations, a mandatory yet difficult step. The present contribution reviews and compares a large selection of estimators for covariance and precision matrices, organized into cla...
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This paper investigates the modeling of risk due to market and funding liquidity by capturing the joint dynamics of three time series: the treasury-Eurodollar spread, the VIX, and a metric derived from the S&P 500 spread. We propose a two-regime mean-reverting model for explaining the behaviour of three time series, which mirror liquidity levels for financial markets. An expectation-maximisation a...
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Estimating covariance matrices in high-dimensional settings is a challenging problem central to modern finance. The sample covariance matrix is well-known to give poor estimates in high dimensions with insufficient samples, and may cause severe risk underestimates of optimized portfolios in the Markowitz framework. In order to provide useful estimates in this regime, a variety of improved covarian...
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Traditional economic models have rigid-form transition functions when modeling time-varying volatility of financial time series data and cannot capture other time-varying dynamics in the financial market. In this paper, combining the Gaussian process state-space model framework and the stochastic volatility (SV) model, we introduce a new Gaussian process regression stochastic volatility (GPRSV) mo...
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This paper develops a novel approach to computation of the probability integrals encountered in derivative pricing using stochastic models estimated from historical data. First, nonparametric probability distribution models are built directly from the data as a solution of a convex optimization problem scalable to very big datasets. Second, these models are used for numerical calculus of probabili...
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Much research has been conducted arguing that tipping points at which complex systems experience phase transitions are difficult to identify. To test the existence of tipping points in financial markets, based on the alternating offer strategic model we propose a network of bargaining agents who mutually either cooperate or compete, where the feedback mechanism between trading and price dynamics i...
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We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We derive a formulation of the problem, discuss several possible integer encoding schemes, and present numerical examples that show high success rates. The formulation incorporates transaction costs (including permanent and temporary market impact), and, significantly, the solution does not require the i...
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This paper considers a statistical signal processing problem involving agent-based models of financial markets, which at a microlevel are driven by socially aware and risk-averse agents. These agents trade (buy or sell) stocks at each trading instant by using the decisions of all previous agents (social learning) in addition to a private (noisy) signal they receive on the value of the stock. We ar...
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In the highly competitive world of modern finance, new derivatives are continually required to take advantage of changes in financial markets, and to hedge businesses against new risks. The research described in this paper aims to accelerate the development and pricing of new derivatives in two different ways. First, new derivatives can be specified mathematically within a general framework, enabl...
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We propose several nonparametric predictors of the mid-price in a limit order book, based on different features constructed from the order book data observed contemporaneously. contemporaneously and in the recent past. We evaluate our predictors in the context of an order execution task by constructing order execution strategies that incorporate these predictors. In our evaluations, we use a large...
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The multi-armed bandit (MAB) problems have been studied mainly under the measure of expected total reward accrued over a horizon of length T . In this paper, we address the issue of risk in MAB problems and develop parallel results under the measure of mean-variance, a commonly adopted risk measure in economics and mathematical finance. We show that the model-specific regret and the model-independ...
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Financial markets typically undergo periods of prosperity followed by periods of stagnation, and this undulation makes it challenging to maintain market efficiency. The efficient market hypothesis (EMH) states that there exist differences in structural complexity in security prices between regular and abnormal situations. Yet, despite a clear link between market acceleration (cf. recession in secu...
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Aims & Scope

The Journal of Selected Topics in Signal Processing (J-STSP) solicits special issues on topics that cover the entire scope of the IEEE Signal Processing Society including the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals by digital or analog devices or techniques.